Student Travel Fellowships to Attend the 2nd Workshop on Resource Discovery

学生旅行奖学金参加第二届资源发现研讨会

• 批准号: 0944126
• 负责人: Zoe Lacroix
• 金额: $ 1.25万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0944126&HistoricalAwards=false
• 关键词: Student; Travel; Fellowships; Attend; 2nd

The second workshop on Resource Discovery (RED) is co-located withthe 35th International Conference on Very Large Data Bases (VLDB)on August 28, 2009, in Lyon, France. This project provides travel fellowships to students enrolled in US universities in order to attend the workshop.The workshop is concerned with the design and development of models and prototypes that support the representation of resources, the discovery of resources on the Web, the identification, localisation, and composition of resources. A resource corresponds to an information source such as a data repository or database management system (e.g., a query form or a textual search engine), a link between resources (an index or hyperlink), or a service such as an application or tool. Resources are characterized by core information including a name, a description of its input and its output (parameters or format), its address, and various additional properties expressed as metadata. Resource discovery is the process of identifying and locating existing resources that have a particular property. Machine-based resource discovery relies on crawling, clustering, and classifying resources discovered on the Web automatically. Resources are organized with respect to metadata that characterize their content (for data sources), their semantics (in terms of ontological classes and relationships), their characteristics (syntactical properties), their performance (with metrics and benchmarks), their quality (curation, reliability, trust), etc. Resource discovery systems allow the expression of queries to identify and locate resources that implement specific tasks. For further information see the project web page at: http://bioinformatics.eas.asu.edu/RED/red2009.html

第二次资源发现研讨会（RED）将于2009年8月28日在法国里昂与第35届超大型数据库国际会议（VLDB）同时举行。该项目为在美国大学注册的学生提供旅行奖学金，以便参加研讨会。研讨会关注支持资源表示的模型和原型的设计和开发，在Web上发现资源，识别，本地化和资源组成。资源对应于诸如数据储存库或数据库管理系统（例如，查询表单或文本搜索引擎）、资源之间的链接（索引或超链接）、或诸如应用程序或工具的服务。资源的特征在于核心信息，包括名称、其输入和输出的描述（参数或格式）、其地址以及表示为元数据的各种附加属性。资源发现是识别和定位具有特定属性的现有资源的过程。基于机器的资源发现依赖于对Web上发现的资源自动进行爬行、聚类和分类。资源是相对于元数据来组织的，元数据表征了它们的内容（对于数据源），它们的语义（在本体类和关系方面），它们的特性（语法属性），它们的性能（具有度量和基准），它们的质量（策展，可靠性，信任）等。欲了解更多信息，请访问项目网页：http://bioinformatics.eas.asu.edu/RED/red2009.html